Data science helps predict candidate behavior. It works to understand when someone might be most likely to move jobs and targets them accordingly. AI and machine learning are also redefining the beginning stages of the hiring process, which can critically contribute to offering a positive candidate experience (while saving hiring professionals valuable time).

Predicting candidate behavior

While you may never be able to fully predict a person’s behavior, there are areas where data science can make intelligent assumptions and aid in your hiring decisions. For example, there’s the potential for technology to analyze resumes, recognize how often someone moves jobs, and ultimately, reveal how likely they are to be interested in a new job opportunity.

Smart technology may look at someone’s career history and notice that they tend to move jobs, on average, every four years; so, if they’re approaching this milestone, they may be more open to changing roles at this time. It can also indicate how long someone will likely stay in your role for (and even how successful they might be).

There are other factors which might influence someone’s decision on whether to change jobs or not — and we’re not talking about salaries or career progression here. In fact, huge life events such as moving into a new home and getting married tend to result in other big changes and there is the potential to pull in data points from social media to make this analysis.

Data science can also understand the types of career paths that candidates are likely to follow. It does this by analyzing career trajectories across millions of different data points in order to spot trends. This can help to guide companies on their hiring efforts and also assist with succession planning.

Taking over the initial stages

As we know, data science can provide valuable insight to hiring managers, and recruiters; but particularly when it comes to streamlining the hiring process and ultimately, reducing their workload. This is most likely to happen during those first stages and touchpoints of the candidate journey, where there are a number of administrative tasks, including sourcing, screening, and scheduling.

The key here is to look at what actually needs to be changed — and not just doing it for the sake of it. For example, if candidates are responding well to your job advertisements, but the hiring teams are drowning in their workload, you’ll want to make sure you aren’t compromising the candidate experience.

Either way, it’s a good idea to consider how data science can help with your hiring process. At Resume-Library, we’re using it to predict how successful a job advertisement will be. By drawing upon application data from hundreds of thousands of jobs posted on your site, we’re able to analyze what jobs are considered ‘successful’. We can then use this information to guide clients on improving their job postings when they upload them to our site.

Improving the candidate experience

We know that competition for the best candidates is rife. After all, less people are actively looking for new jobs, and this is putting pressure on companies and staffing agencies to proactively source top talent and ensure they offer a positive hiring experience that candidates enjoy.

In fact, hiring professionals need to focus more on adding value to their conversations with candidates. What can they do to set themselves apart from other companies that are hiring?

A good place to start when it comes to using data is analyzing your current hiring process. Are there any major barriers that are impacting your recruitment efforts? For example, you may find that people are clicking on your job advertisements, but are abandoning the application process halfway through because it’s too difficult to navigate or taking too long. If this is the case, you can then look at making positive improvements.

Ultimately, leveraging such data can help you improve the value of each encounter you have with a candidate; so consider what changes you can make.

Transform your hiring process with data science

There are a number of factors that are influencing the U.S. labor market right now. But one thing’s for sure; data science is only growing in prominence when it comes to helping companies improve their hiring efforts. Whether you’re already using big data, AI, and machine learning technology to boost your hiring process, or you’re considering how you can implement it, it’s definitely worth investing in.

The post How data science has the potential to transform the hiring process: part 1 of 2 appeared first on Leoforce.

From a job board provider perspective:

There are many factors that are influencing the world of recruitment right now. From ongoing skills shortages and tackling unconscious bias, to new technologies and record employment; hiring professionals are under pressure to source the right candidates, in the right way.

Indeed, one of the key areas that’s on everyone’s lips is machine learning and AI. Ultimately, machine learning seeks to help employers automate some of the more repetitive areas of the recruitment process. And for that reason, it’s an area that many organizations are keen to explore.

But how is machine learning actually impacting (and improving) companies’ hiring practices? With promises that it can boost your hiring efforts and remove some of the more arduous tasks associated with recruitment, it’s no wonder that businesses want a piece of the pie. So, let’s discuss just some of the ways this is happening.

Improving Job Matches for Candidates

At Resume-Library, we’ve been using assisted machine learning to help improve job matches for candidates. This works by manually rating job search results against popular search terms. So, for example, if a candidate were to search ‘substitute teachers’ and the results included jobs for ‘substitute nurses’, this would receive a one star rating out of five.

Once we complete this stage, this information is fed into the ‘machine’, which goes on to identify patterns for good and bad jobs. The logic is then applied to all jobs on the site to ensure that candidates are presented with only the most relevant search results.

This approach to machine learning is helping to improve matches for candidates, while also pushing employers’ jobs in front of the right people. Ultimately, this will ensure companies receive more applications from the most relevant candidates. So, it’s worth checking in with your vendors to find out whether they’re using machine learning to improve your candidate matches.

Analyzing the Success of Job Adverts and Identifying Patterns for Future Posts

Your job advertisement is one of the most important parts of your hiring process. After all, it’s the first insight a candidate has of your company, so it’s crucial to get it right. The good news is that this is an area where machine learning is playing a key role.

Of course, AI and machine learning can never take away the entire task of writing your job adverts; this still requires a human touch. However, it can help to analyze your postings and tell you why some adverts work and others don’t. This might be down to language patterns, tone of voice and even any gender specific wordings that might be putting off applicants.

It then uses this information to make suggestions on what you should (and shouldn’t) include in future posts. For organizations that are struggling to recruit, this can provide valuable insights that make a real difference to your hiring process; so it’s definitely something to explore.

Screening Resumes and Assessing For Cultural Fit

Another key area where machine learning is impacting hiring is of course throughout the screening process. Time and money is precious and both can be lost if your screening process isn’t as efficient as possible. The good news is technology is making it easier than ever to screen resumes and assess candidates for cultural fit.

While screening candidates’ skills against a job description is nothing new, the fact that these tools are now able to assess how well a candidate will fit into the company culture is particularly impressive. After all, as it becomes harder to source top talent, companies are increasingly hiring on potential rather than experience. So, being able to assess someone on how well they’ll fit into your business, and what they can bring to the table, can be extremely beneficial.

Another key benefit of using AI and machine learning in this way is that it can help to remove human bias throughout the screening process.  Whether we mean to or not, we’re all guilty of judging a book by its cover; so anything we can do to prevent this from happening can certainly help.

Managing Relations with Candidates

Candidate experience is always going to be an important part of the hiring process. As mentioned above, it’s harder than ever to recruit right now and that’s why it’s vital that companies focus on candidate engagement.

This covers each stage of the user journey. From answering candidate questions at the application stage, to staying in contact pre and post interview; keeping candidates happy and informed should be a priority.

One of the trends we’re noticing in this area is the rise in chatbots. Many organizations are using these to help interact with candidates; for example, by providing more information about a job, or even scheduling in an interview. Again, this can save massive amounts of time when recruiting, ultimately having a positive impact on your hiring efforts.

What Are You Doing to Improve Your Hiring Efforts?

Overall, it’s clear that there are a numbers of ways in which AI and machine learning are impacting hiring practises for the better. From improving job matches and job adverts, to screening candidates and managing relations with them, technology is ultimately making the process of sourcing and hiring individuals much easier.

However, it’s important to note that each area should be closely monitored to avoid any form of bias. Indeed, some organizations have hit the headlines for all the wrong reasons when it comes to using AI in their hiring process; and you don’t want to be one of them.

But that’s why it’s still important to include a human element when hiring. Who knows if it will ever be a fully automated process, but what we do know is that there are some great developments being made across the industry.

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